{"product_id":"artificial-intelligence-in-healthcare-intellectual-property-landscape","title":"Artificial Intelligence in Healthcare: Intellectual Property Landscape","description":"\u003cp\u003eArtificial Intelligence in Healthcare: Intellectual Property Landscape (Featuring Historical and Contemporary Patent Filing Trends, Prior Art Search Expressions, Patent Valuation Analysis, Patentability, Freedom to Operate, Pockets of Innovation, Existing White Spaces, and Claims Analysis)\u003c\/p\u003e\n\n\u003cp\u003eThe global healthcare sector has been overtly reluctant to embrace technology. This may partially be due to the failure of early digitization efforts, which were fraught with challenges and turned out to be more of a liability rather than a path forward. In fact, according to a study, clinicians ended up spending more than twice as much time on administrative work (49%), such as updating electronic medical records, than on seeing patients (27%). The delivery of modern healthcare services is, therefore, still in many ways obsolete, relying on analog systems and manual execution on simple, repetitive operations. This situation is challenging for both healthcare providers (resulting in long and arduous work hours, causing medical staff to burn themselves out) and consumers (which is reflected in hurried, inappropriate diagnosis, lack of proper care and delays in treatment administration). Further, experts have predicted that if things don’t change significantly, there is likely to be a severe shortage of healthcare workers in the mid to long term. Similar inefficiencies exist in the pharmaceutical development segment as well, with over USD 800 million being spent on drug discovery alone; a typical product development cycle in this domain lasts close to a decade and costs USD 2.5 billion, on average. However, advances in automation and intuitive software have made it possible for stakeholders to markedly improve operational efficiencies and cut-down on both operational and administrative expenses.\u003c\/p\u003e \n\n\u003cp\u003eToday, self-learning algorithms are being used to develop AI that can not only help automate various simple and complex tasks but can also assist clinicians in making critical diagnosis \/ treatment related decisions. It is estimated that over 33% of the tasks that are performed manually by clinicians can be automated, and there are artificially intelligent solutions that are capable of carrying out specialized functions, such as patient triage, without human supervision. Over the last couple of decades, computer scientists and medical researchers have successfully demonstrated the applications of AI in several diverse aspects of healthcare delivery, including (but not limited to) surgery, drug discovery and hospital \/ patient data management. The use of self-improving algorithms also guarantees cost savings; experts estimate that savings worth over USD 150 billion can be achieved by 2026, through the adoption of AI-enabled technologies, in the US alone. As a result, a lot of capital and effort are being invested by innovators across the world in this burgeoning field of research. This report attempts to identify key trends that describe the pace and focus of innovation related to healthcare focused AI technologies and solutions.\u003c\/p\u003e \n\n\u003cp\u003eSCOPE OF THE REPORT\u003cbr\u003e\nThe “Artificial Intelligence in Healthcare: Intellectual Property Landscape” report features an extensive study of the historical and current collection of granted patents, patent applications and affiliated documents associated with the upcoming suite of intuitive software and automation enabling solutions, which are designed for use within the healthcare industry. The information in this report has been presented across two deliverables, namely an Excel sheet, featuring an interactive dashboard, and a PowerPoint presentation, summarizing the ongoing activity in this domain, and key insights drawn from the available data. The report features the following details:\u003cbr\u003e\n?\tOverall Intellectual Property Landscape\u003cbr\u003e\nAn in-depth review of the various patents and affiliated IP documents that have been published related to technologies and methods associated with the healthcare-related applications of AI, featuring key insights on historical and recent trends.\u003cbr\u003e\n?\tPopular \/ Relevant Prior Art Search Expressions\u003cbr\u003e\nAn examination of IP literature, identifying key words and phrases that are used to describe innovations involving the use of AI and other intuitive algorithms for healthcare-focused applications, including information on historical usage in IP filings, key affiliated terms (which can be used to further identify similar innovations), and other related trends.\u003cbr\u003e\n?\tPatent Valuation Analysis\u003cbr\u003e\nA competitive benchmarking and valuation analysis of the IP documents published in this field of innovation, taking into account important parameters, such as type of IP document, year of application, time to expiry, number of citations and jurisdiction (factoring in regional GDP).\u003cbr\u003e\n?\tPatentability and Freedom to Operate\u003cbr\u003e\nA systematic approach to identifying relevant areas of innovation by analyzing published IP documents, defining the uniqueness patented \/ patent pending innovations, understanding the scope of patentability in this domain, and pinpointing jurisdictions where new and \/ or modified claims may be filed without infringing on existing IP. \u003cbr\u003e\n?\tAnalysis of Patent Applications\u003cbr\u003e\nA detailed summary of the patent applications that were filed across different jurisdictions and their relative value in the IP ecosystem. The analysis segregates the intellectual capital in terms of area of innovation and intended applications, thereby, offering the means to understand key areas of research and identify innovation-specific IP filing trends.\u003cbr\u003e\n?\tAnalysis of Granted Patents\u003cbr\u003e\nAn elaborate summary of the granted patents across different jurisdictions and their relative value in the IP ecosystem. The analysis uses a slightly more specific segregation criteria, based on type of product \/ solution and intended applications; this offers the means to identify unique innovations that presently have marketing exclusivity and explore future opportunities to enter into promising product markets, once their patents expire. \u003cbr\u003e\n?\tPockets of Innovation and White Spaces\u003cbr\u003e\nAn insightful analysis of the various CPC symbols mentioned in the published IP literature used and their affiliated families, in order to identify historical and existing pockets of innovation (based on the functional area \/ industry described by the elaborate and systematic system of classifying IP); the analysis also features a discussion on the prevalent white spaces (based on CPC symbols) in this area of research.\u003cbr\u003e\n?\tClaims Analysis\u003cbr\u003e\nOne of the key objectives of the report was to analyze and summarize key inferences from the independent claims mentioned in the granted, active patents in the entire dataset. Using a systematic segregation approach, we have analyzed trends associated with [A] the preamble, [B] type of patent (technology patent or method patent), [C] type of claim (open ended claim or closed ended claim) and [D] key elements of a claim (individual aspects of an innovation that are covered in a singular claim).\u003c\/p\u003e \n\n\u003cp\u003eRESEARCH METHODOLOGY\u003cbr\u003e\nThe data presented in this report has been gathered via secondary research and analyzed via proprietary methods \/ tools to develop a detailed perspective on the current status of the innovative advances in this domain and affiliated developer landscape that is spread across different global regions. Where possible, the available data has been checked for accuracy from multiple sources of information.\u003c\/p\u003e\n\n\u003cp\u003eThe secondary sources of information include \u003cbr\u003e\n?\tCompany websites \u003cbr\u003e\n?\tAnnual reports\u003cbr\u003e\n?\tPatent information aggregator portals\u003cbr\u003e\n?\tIndustry databases\u003cbr\u003e\n?\tPress releases \u003cbr\u003e\n?\tIndustry analysts’ views\u003c\/p\u003e\n\n\u003cp\u003eThe insights presented are solely based on our knowledge, research and understanding of the relevant market, as gathered from various secondary sources of information.\u003c\/p\u003e\n\n\u003cp\u003eDELIVERABLE OUTLINES\u003cbr\u003e\nExcel Deliverable\u003cbr\u003e\nSheet 1 of the spreadsheet features details on how the input data for this project was collated, including the search strings used to query a popular patent database, data segregation guidelines and IP category definition, and noise removal criteria.\u003c\/p\u003e\n\n\u003cp\u003eSheet 2 is a summary MS Excel dashboard, offering a detailed graphical perspective of the intellectual property landscape of AI-enabled technologies and solutions for use in the healthcare industry. It includes pictorial representations of the [A] overall patent landscape, [B] IP valuation-related insights, [C] insights on patentability and freedom to operate, [D] key trends related to patent applications, [E] key trends related to granted patents, and [F] impact of the COVID-19 pandemic on IP filing \/ grant.\u003c\/p\u003e\n\n\u003cp\u003eSheet 3 is an elaborate tabular representation of the overall IP landscape, featuring information on the various patent application- and granted patent-related documents that have been published since 1995.\u003c\/p\u003e\n\n\u003cp\u003eSheet 4 includes a tabular representation of key words and phrases that are used to describe innovations involving the use of AI and other intuitive algorithms for healthcare-focused applications.\u003c\/p\u003e \n\n\u003cp\u003eSheet 5 is a subset of sheet 3, featuring all the patent applications, covering innovation related to AI-enabled software \/ technologies for healthcare applications.\u003c\/p\u003e\n\n\u003cp\u003eSheet 6 is a subset of sheet 3, featuring all the granted patents, covering innovation related to AI-enabled software \/ technologies for healthcare applications.\u003c\/p\u003e \n\n\u003cp\u003eSheet 7 is an insightful summary of key inferences from the independent claims mentioned in the granted, active patents in the dataset. We have used a systematic segregation approach, to analyze trends associated with the preamble, type of patent (technology patent or method patent), type of claim (open ended claim or closed ended claim) and key elements of a claim (individual aspects of an innovation that are covered in a singular claim).\u003c\/p\u003e\n\n\u003cp\u003eSheet 8 features insights related to patentability and freedom to operate dataset in the contemporary IP landscape, related to AI enabled solutions for healthcare use.\u003c\/p\u003e\n\n\u003cp\u003eSheet 9 is also a subset of sheet 3, which includes a tabulated representation of all IP documents that were published during the COVID-19 pandemic.\u003c\/p\u003e\t\n\n\u003cp\u003eSheet 10 is an appendix which includes pivot tables that drive the interactive elements in sheet 2.\u003c\/p\u003e \n\n\u003cp\u003eSheet 11 is an appendix, featuring country codes corresponding to the jurisdictions mentioned in the dataset.\u003c\/p\u003e \n\n\u003cp\u003ePowerPoint Deliverable\u003cbr\u003e\nSection I features an executive summary of the key insights generated from analyzing the intellectual property landscape of AI technologies and solutions designed for healthcare-related applications.\u003c\/p\u003e\n\n\u003cp\u003eSection II provides important details related to the healthcare applications of AI and affiliated intuitive data processing algorithms, including key innovation related definitions, contemporary and promising future application areas, and detailed profiles of some the popular AI solutions developed by established players in the field, such as IBM and Google (DeepMind Technologies). \u003cbr\u003e\nThis section includes a review of the various patents and IP documents that have been published related to technologies and methods associated with the healthcare-related applications of AI, featuring key insights on historical and recent trends.\u003c\/p\u003e\n\n\u003cp\u003eIt includes an insightful examination of IP literature, identifying key words and phrases that are used to describe innovations involving the use of AI and other intuitive algorithms for healthcare-focused applications, including information on historical usage in IP filings, key affiliated terms (which can be used to further identify similar innovations), and other related trends.\u003c\/p\u003e\n\n\u003cp\u003eIn addition, it features a competitive benchmarking and valuation analysis of the IP documents published in this field of innovation, taking into account important parameters, such as type of IP document, year of application, time to expiry, number of citations and jurisdiction (factoring in regional GDP).\u003c\/p\u003e\n\n\u003cp\u003eSection III describes a systematic approach to identifying relevant areas of innovation by analyzing published IP documents, defining the uniqueness patented \/ patent pending innovations, understanding the scope of patentability in this domain, and pinpointing jurisdictions where new and \/ or modified claims may be filed without infringing on existing IP.\u003c\/p\u003e\n\n\u003cp\u003eSection IV provides a detailed summary of the patent applications that were filed across different jurisdictions and their relative value in the IP ecosystem. The analysis segregates the intellectual capital in terms of area of innovation and intended applications, thereby, offering the means to understand key areas of research and identify innovation-specific IP filing trends.\u003c\/p\u003e\n\n\u003cp\u003eSection V is an elaborate summary of the granted patents across different jurisdictions and their relative value in the IP ecosystem. The analysis uses a slightly more specific segregation criteria, based on type of product \/ solution and intended applications; this offers the means to identify unique innovations that presently have marketing exclusivity and explore future opportunities to enter into promising product markets, once their patents expire.\u003c\/p\u003e\n\n\u003cp\u003eIt includes an insightful analysis of the various CPC symbols mentioned in the published IP literature used and their affiliated families, in order to identify historical and existing pockets of innovation (based on the functional area \/ industry described by the elaborate and systematic system of classifying IP); the analysis also features a discussion on the prevalent white spaces (based on CPC symbols) in this area of research.\u003c\/p\u003e\n\n\u003cp\u003eSection VI offers an informed perspective on the IP filing and grant trends during the COVID-19 pandemic, when the demand for automating healthcare services was at its peak. Further, it provides insights on anticipated developments and trends that are likely to shape the future of the AI in healthcare market.\u003c\/p\u003e \n\n\u003cp\u003eLIST OF COMPANIES \/ LIST OF COMPANIES AND ORGANIZATIONS\u003c\/p\u003e\n\n\u003cp\u003eThe    following companies and organizations have been mentioned in the report.\u003c\/p\u003e\n\n\u003cp\u003e1.\t20\/20 GeneSystems\u003cbr\u003e\n2.\t23andMe\u003cbr\u003e\n3.\t360 Knee Systems\u003cbr\u003e\n4.\t3D Smile\u003cbr\u003e\n5.\t3M \u003cbr\u003e\n6.\t3SI Security Systems\u003cbr\u003e\n7.\t410Ai\u003cbr\u003e\n8.\t7D Surgical\u003cbr\u003e\n9.\tAarhus University\u003cbr\u003e\n10.\tAbbott\u003cbr\u003e\n11.\tAbiomed\u003cbr\u003e\n12.\tAbraxis Bioscience\u003cbr\u003e\n13.\tAccenture\u003cbr\u003e\n14.\tAccess Radiology\u003cbr\u003e\n15.\tAccessible Conseils\u003cbr\u003e\n16.\tActo\u003cbr\u003e\n17.\tAcupath Laboratories\u003cbr\u003e\n18.\tAdvanced Medical Imaging Development\u003cbr\u003e\n19.\tAdvanced Mobile Payment\u003cbr\u003e\n20.\tAdvanced Neuromodulation Systems\u003cbr\u003e\n21.\tAdvanced Solutions Life Sciences\u003cbr\u003e\n22.\tAdviNOW Medical\u003cbr\u003e\n23.\tAdvisory Board\u003cbr\u003e\n24.\tAetharAI\u003cbr\u003e\n25.\tAffymetrix\u003cbr\u003e\n26.\tAgency for Science, Technology and Research\u003cbr\u003e\n27.\tAgilent Technologies\u003cbr\u003e\n28.\tAgility Capital\u003cbr\u003e\n29.\tAgios Pharmaceuticals\u003cbr\u003e\n30.\tAgricultural Information Institute (AII) of Chinese Academy of Agricultural Sciences\u003cbr\u003e\n31.\tAI Fluidics\u003cbr\u003e\n32.\tAI Technology\u003cbr\u003e\n33.\tAidot\u003cbr\u003e\n34.\tAir Products\u003cbr\u003e\n35.\tAjinomoto\u003cbr\u003e\n36.\tAkili Biosystems\u003cbr\u003e\n37.\tAkili Interactive\u003cbr\u003e\n38.\tAkitra\u003cbr\u003e\n39.\tAktana\u003cbr\u003e\n40.\tAlayaCare\u003cbr\u003e\n41.\tAlcaris Theranostics\u003cbr\u003e\n42.\tAlegeus\u003cbr\u003e\n43.\tAlgotec\u003cbr\u003e\n44.\tAlibaba Group\u003cbr\u003e\n45.\tAlign Technology\u003cbr\u003e\n46.\tAlignCare\u003cbr\u003e\n47.\tAlipay Information Technology\u003cbr\u003e\n48.\tAlivia Capital\u003cbr\u003e\n49.\tAllegheny-Singer Research Institute\u003cbr\u003e\n50.\tAllen Institute\u003cbr\u003e\n51.\tAllOne Health\u003cbr\u003e\n52.\tAllscripts\u003cbr\u003e\n53.\tAltair\u003cbr\u003e\n54.\tAltheaDX\u003cbr\u003e\n55.\tAltrics\u003cbr\u003e\n56.\tAlverix \u003cbr\u003e\n57.\tAlverix \u003cbr\u003e\n58.\tAlyce Health\u003cbr\u003e\n59.\tAmbry Genetics\u003cbr\u003e\n60.\tAmeican TelePhysicians\u003cbr\u003e\n61.\tAmerican Board of Family Medicine\u003cbr\u003e\n62.\tAmericrop Investments\u003cbr\u003e\n63.\tAmino\u003cbr\u003e\n64.\tAmpel BioSolutions\u003cbr\u003e\n65.\tAmrita Vishwa Vidyapeetham\u003cbr\u003e\n66.\tAmuseneering\u003cbr\u003e\n67.\tAncestry\u003cbr\u003e\n68.\tAnswers\u003cbr\u003e\n69.\tApixio\u003cbr\u003e\n70.\tApogee Informatics\u003cbr\u003e\n71.\tApostle\u003cbr\u003e\n72.\tApplera Corporation\u003cbr\u003e\n73.\tApplied Brain Research\u003cbr\u003e\n74.\tApplied Invention\u003cbr\u003e\n75.\tApplied Investments\u003cbr\u003e\n76.\tApplied Minds\u003cbr\u003e\n77.\tApplied Proteomics\u003cbr\u003e\n78.\tAPT International Business Sciences\u003cbr\u003e\n79.\tAptar\u003cbr\u003e\n80.\tARC Devices\u003cbr\u003e\n81.\tArchimedes\u003cbr\u003e\n82.\tArchitecture Technology Corporation\u003cbr\u003e\n83.\tArgo\u003cbr\u003e\n84.\tArizona Board of Regents, Arizona State University\u003cbr\u003e\n85.\tArmadaGlobal\u003cbr\u003e\n86.\tArmadaHealth\u003cbr\u003e\n87.\tArterys\u003cbr\u003e\n88.\tArtificial Learning Systems\u003cbr\u003e\n89.\tAscriptus\u003cbr\u003e\n90.\tASP Global\u003cbr\u003e\n91.\tAspen Neuroscience\u003cbr\u003e\n92.\tAspira Women's Health\u003cbr\u003e\n93.\tAsthma Signals\u003cbr\u003e\n94.\tAstrazeneca\u003cbr\u003e\n95.\tAstrid Pharma\u003cbr\u003e\n96.\tAT \u0026amp; T Intellectual Property\u003cbr\u003e\n97.\tAthelas\u003cbr\u003e\n98.\tATONARP\u003cbr\u003e\n99.\tAugmedix\u003cbr\u003e\n100.\tAUM Cardiovascular \u003cbr\u003e\n101.\tAureon Laboratories\u003cbr\u003e\n102.\tAustralian Institute of Robotic Orthopaedics\u003cbr\u003e\n103.\tAvago Technologies\u003cbr\u003e\n104.\tAventusoft\u003cbr\u003e\n105.\tAveva\u003cbr\u003e\n106.\tAviir\u003cbr\u003e\n107.\tAzova\u003cbr\u003e\n108.\tBabylon\u003cbr\u003e\n109.\tBagne-Miller Enterprises\u003cbr\u003e\n110.\tBaidu USA\u003cbr\u003e\n111.\tBaker Heart and Diabetes Institute\u003cbr\u003e\n112.\tBanner Health\u003cbr\u003e\n113.\tBanyan Biomarkers\u003cbr\u003e\n114.\tBaseHealth\u003cbr\u003e\n115.\tBASF Plant Science\u003cbr\u003e\n116.\tBattelle Memorial Institute\u003cbr\u003e\n117.\tBaxalta\u003cbr\u003e\n118.\tBaxter International\u003cbr\u003e\n119.\tBayer\u003cbr\u003e\n120.\tBayer\u003cbr\u003e\n121.\tBaylor College of Medicine\u003cbr\u003e\n122.\tBean Holdings\u003cbr\u003e\n123.\tBechtel\u003cbr\u003e\n124.\tBeckman Coulter Diagnostics\u003cbr\u003e\n125.\tBecton Dickinson\u003cbr\u003e\n126.\tBeijing Boyuan Xingkang Science and Technology\u003cbr\u003e\n127.\tBeijing Guhai Tianmu Biomedical Technology\u003cbr\u003e\n128.\tBeijing Institute of Genomics\u003cbr\u003e\n129.\tBeijing Medical Cloud Technology\u003cbr\u003e\n130.\tBeijing Muyebang Technology\u003cbr\u003e\n131.\tBeijing Qiji Biotechnologynology\u003cbr\u003e\n132.\tBeijing Tianhe Wisdom Health \u003cbr\u003e\n133.\tBeijing Tuberculosis And Thoracic Tumor Research Institute\u003cbr\u003e\n134.\tBeijing University of Technology\u003cbr\u003e\n135.\tBeijing Wanfang Data\u003cbr\u003e\n136.\tBeijing Xbentury Network Technology\u003cbr\u003e\n137.\tBeijing Xiangxin Biotechnology\u003cbr\u003e\n138.\tBeijing Xiangxin Medical Technology\u003cbr\u003e\n139.\tBeijing Yikang Medical Technology\u003cbr\u003e\n140.\tBellsouth Intellect \u003cbr\u003e\n141.\tBenevis Informatics\u003cbr\u003e\n142.\tBenevolentAI\u003cbr\u003e\n143.\tBerg Health\u003cbr\u003e\n144.\tBerkeley Lights\u003cbr\u003e\n145.\tBerlin Institute for Health Research\u003cbr\u003e\n146.\tBespoke\u003cbr\u003e\n147.\tBeta Bionics\u003cbr\u003e\n148.\tBeyondspring Pharmaceuticals\u003cbr\u003e\n149.\tBhogar \u003cbr\u003e\n150.\tBio Imaging Korea\u003cbr\u003e\n151.\tBio Synergy Research Center\u003cbr\u003e\n152.\tBioanalytics Group\u003cbr\u003e\n153.\tBioanalytix\u003cbr\u003e\n154.\tBioarray Genetics\u003cbr\u003e\n155.\tBiofield\u003cbr\u003e\n156.\tBioinfra\u003cbr\u003e\n157.\tBioinfra Life Science\u003cbr\u003e\n158.\tBiokaizen\u003cbr\u003e\n159.\tBiomar \u003cbr\u003e\n160.\tBiome\u003cbr\u003e\n161.\tBionous\u003cbr\u003e\n162.\tBiophysical Corporation\u003cbr\u003e\n163.\tBioretics\u003cbr\u003e\n164.\tBios Health\u003cbr\u003e\n165.\tBiosensors International\u003cbr\u003e\n166.\tBiosymetrics\u003cbr\u003e\n167.\tBiotempus\u003cbr\u003e\n168.\tBio-Thera\u003cbr\u003e\n169.\tBiotie Therapies\u003cbr\u003e\n170.\tBiowulf Technologies\u003cbr\u003e\n171.\tBired Imaging\u003cbr\u003e\n172.\tBlackthaorn Therapeutics\u003cbr\u003e\n173.\tBloom Technologies\u003cbr\u003e\n174.\tBluarc Capital\u003cbr\u003e\n175.\tBluarc Health\u003cbr\u003e\n176.\tBlue Note Therapeutics\u003cbr\u003e\n177.\tBluestar Genomics\u003cbr\u003e\n178.\tBOE Technology\u003cbr\u003e\n179.\tBomdic\u003cbr\u003e\n180.\tBosch\u003cbr\u003e\n181.\tBose Corporation\u003cbr\u003e\n182.\tBoston Research Corporation\u003cbr\u003e\n183.\tBoston Scientific Neuromodulation \u003cbr\u003e\n184.\tBostongene\u003cbr\u003e\n185.\tBracco Imaging\u003cbr\u003e\n186.\tBrain Power Systems\u003cbr\u003e\n187.\tBrain Trust Innovations\u003cbr\u003e\n188.\tBrainbox Solutions \u003cbr\u003e\n189.\tBrainchip Holdings\u003cbr\u003e\n190.\tBrainehealth\u003cbr\u003e\n191.\tBrainlab\u003cbr\u003e\n192.\tBrainwide Solutions\u003cbr\u003e\n193.\tBrigham and Women's Hospital\u003cbr\u003e\n194.\tBrighterion\u003cbr\u003e\n195.\tBritescan\u003cbr\u003e\n196.\tBroad Institute\u003cbr\u003e\n197.\tBroadcom\u003cbr\u003e\n198.\tBuck Institute for Research on Aging\u003cbr\u003e\n199.\tBusiness Expectations \u003cbr\u003e\n200.\tBuzzpole\u003cbr\u003e\n201.\tCaduceus Systems\u003cbr\u003e\n202.\tCaldwell Intellectual Property Law\u003cbr\u003e\n203.\tCalifornia Institute of Technology\u003cbr\u003e\n204.\tCambia Health Solutions\u003cbr\u003e\n205.\tCambridge Bio-Augmentation Systems\u003cbr\u003e\n206.\tCancer Commons\u003cbr\u003e\n207.\tCancer Prevention Pharmaceuticals\u003cbr\u003e\n208.\tCannabics Pharmaceuticals\u003cbr\u003e\n209.\tCanon Medical Systems\u003cbr\u003e\n210.\tCanon USA\u003cbr\u003e\n211.\tCapital.com\u003cbr\u003e\n212.\tCapitalbio Technology\u003cbr\u003e\n213.\tCardiocom\u003cbr\u003e\n214.\tCardioDx\u003cbr\u003e\n215.\tCareFusion\u003cbr\u003e\n216.\tCareoregon\u003cbr\u003e\n217.\tCarepartners Plus\u003cbr\u003e\n218.\tCaris Life Sciences\u003cbr\u003e\n219.\tCarlsmed\u003cbr\u003e\n220.\tCarrot\u003cbr\u003e\n221.\tCase Western Reserve University\u003cbr\u003e\n222.\tCasio\u003cbr\u003e\n223.\tCatalia Health\u003cbr\u003e\n224.\tCatalight Foundation\u003cbr\u003e\n225.\tCaterpillar\u003cbr\u003e\n226.\tCatholic University of Korea\u003cbr\u003e\n227.\tCC\u0026amp;I Research\u003cbr\u003e\n228.\tCedars-Sinai Medical Center\u003cbr\u003e\n229.\tCelgene\u003cbr\u003e\n230.\tCellanyx\u003cbr\u003e\n231.\tCellcarta\u003cbr\u003e\n232.\tCell-El Therapeutics\u003cbr\u003e\n233.\tCellmic\u003cbr\u003e\n234.\tCellomics\u003cbr\u003e\n235.\tCellworks Life\u003cbr\u003e\n236.\tCelmatix\u003cbr\u003e\n237.\tCenter for Eye Research, Australia\u003cbr\u003e\n238.\tCenter for Medical Interoperability\u003cbr\u003e\n239.\tCentriHealth\u003cbr\u003e\n240.\tCenturylink\u003cbr\u003e\n241.\tCeridian\u003cbr\u003e\n242.\tCerner\u003cbr\u003e\n243.\tCerner\u003cbr\u003e\n244.\tCerner\u003cbr\u003e\n245.\tCerora\u003cbr\u003e\n246.\tCertara\u003cbr\u003e\n247.\tCES\u003cbr\u003e\n248.\tChamberlin Edmonds \u0026amp; Associates\u003cbr\u003e\n249.\tChampalimaud Foundation\u003cbr\u003e\n250.\tChan Zuckerberg Biohub\u003cbr\u003e\n251.\tChang Gung University\u003cbr\u003e\n252.\tChangchun Meihe Science and Technology Development \u003cbr\u003e\n253.\tChange Healthcare\u003cbr\u003e\n254.\tChange Healthcare\u003cbr\u003e\n255.\tChase Therapeutics\u003cbr\u003e\n256.\tChen Technology\u003cbr\u003e\n257.\tChildren's Hospital and Medical Center\u003cbr\u003e\n258.\tChildren's Hospital of Fudan University\u003cbr\u003e\n259.\tChildren's Medical Center\u003cbr\u003e\n260.\tChildren's National Medical Center\u003cbr\u003e\n261.\tChina Institute for Radiation Protection\u003cbr\u003e\n262.\tChina Medical University \u003cbr\u003e\n263.\tChina Telecom\u003cbr\u003e\n264.\tChongqing University Cancer Hospital\u003cbr\u003e\n265.\tCigna\u003cbr\u003e\n266.\tCincinati Children's Hospital Medical Center\u003cbr\u003e\n267.\tCipher Gene\u003cbr\u003e\n268.\tCirtec Medical\u003cbr\u003e\n269.\tCiti\u003cbr\u003e\n270.\tCitrix\u003cbr\u003e\n271.\tCity University of Hong Kong\u003cbr\u003e\n272.\tCixi Institute of Biomedical Engineering\u003cbr\u003e\n273.\tClarify Health Solutions\u003cbr\u003e\n274.\tClarion\u003cbr\u003e\n275.\tCLAS Healthcare\u003cbr\u003e\n276.\tClearAg\u003cbr\u003e\n277.\tCleave Therapeutics\u003cbr\u003e\n278.\tCleveland Clinic\u003cbr\u003e\n279.\tCleveland Heartlab\u003cbr\u003e\n280.\tClinical Genomics\u003cbr\u003e\n281.\tClinicalbox \u003cbr\u003e\n282.\tClover Health\u003cbr\u003e\n283.\tCodexis Mayflower Holdings\u003cbr\u003e\n284.\tCofactor Genomics\u003cbr\u003e\n285.\tCogent Biosciences\u003cbr\u003e\n286.\tCogito\u003cbr\u003e\n287.\tCognitiveScale\u003cbr\u003e\n288.\tCognoa\u003cbr\u003e\n289.\tCohero Health\u003cbr\u003e\n290.\tColibri Technologies\u003cbr\u003e\n291.\tCollective Health\u003cbr\u003e\n292.\tColon Health Centers of America\u003cbr\u003e\n293.\tColor\u003cbr\u003e\n294.\tColossio\u003cbr\u003e\n295.\tCommonwealth Scientific and Industrial Research Organisation\u003cbr\u003e\n296.\tCommunity Care of North Carolina\u003cbr\u003e\n297.\tComplexData\u003cbr\u003e\n298.\tCompressus\u003cbr\u003e\n299.\tCompressus\u003cbr\u003e\n300.\tComputer Technology Associates\u003cbr\u003e\n301.\tConduent\u003cbr\u003e\n302.\tConduent\u003cbr\u003e\n303.\tConifer Health Solutions\u003cbr\u003e\n304.\tConnance\u003cbr\u003e\n305.\tConnectix Corporation\u003cbr\u003e\n306.\tConnSante Biotech\u003cbr\u003e\n307.\tConquerAb\u003cbr\u003e\n308.\tCooperSurgical\u003cbr\u003e\n309.\tCoreMedica Europe\u003cbr\u003e\n310.\tCorista\u003cbr\u003e\n311.\tCorista\u003cbr\u003e\n312.\tCornell University\u003cbr\u003e\n313.\tCorrelogic Systems\u003cbr\u003e\n314.\tCortexXus\u003cbr\u003e\n315.\tCorVista Health\u003cbr\u003e\n316.\tCOTA\u003cbr\u003e\n317.\tCotinga Pharmaceuticals\u003cbr\u003e\n318.\tCouncil of Scientific and Industrial Research\u003cbr\u003e\n319.\tCounsyl\u003cbr\u003e\n320.\tCovera Health\u003cbr\u003e\n321.\tCovidien\u003cbr\u003e\n322.\tCoyne Scientific\u003cbr\u003e\n323.\tCrescendo Bioscience\u003cbr\u003e\n324.\tCritical Connection\u003cbr\u003e\n325.\tCrowe\u003cbr\u003e\n326.\tCrowley Davis Research\u003cbr\u003e\n327.\tCSC Holdings\u003cbr\u003e\n328.\tCSTS Health Care\u003cbr\u003e\n329.\tCTRL-Labs\u003cbr\u003e\n330.\tCURA4U\u003cbr\u003e\n331.\tCurai Health\u003cbr\u003e\n332.\tCuramatix Healthcare\u003cbr\u003e\n333.\tCurelon\u003cbr\u003e\n334.\tCuremark\u003cbr\u003e\n335.\tCureMatch\u003cbr\u003e\n336.\tCurneu MedTech Innovation\u003cbr\u003e\n337.\tCutaneous Information Technologies\u003cbr\u003e\n338.\tCyberdontics\u003cbr\u003e\n339.\tCyberkinetics Neurotechnology Systems\u003cbr\u003e\n340.\tCyrcadia\u003cbr\u003e\n341.\tCyrcadia\u003cbr\u003e\n342.\tCyrcadia\u003cbr\u003e\n343.\tCytognomix\u003cbr\u003e\n344.\tCytokinetics\u003cbr\u003e\n345.\tD\u0026amp;P Biotech\u003cbr\u003e\n346.\tDacadoo\u003cbr\u003e\n347.\tDaegu Gyeongbuk Institute of Science and Technology\u003cbr\u003e\n348.\tDaiwa House\u003cbr\u003e\n349.\tDako\u003cbr\u003e\n350.\tDana-Farber Cancer Institute\u003cbr\u003e\n351.\tDartmouth College\u003cbr\u003e\n352.\tDatagenno Interactive Research\u003cbr\u003e\n353.\tDatCard\u003cbr\u003e\n354.\tDayaMed\u003cbr\u003e\n355.\tDecipher by Veracyte\u003cbr\u003e\n356.\tDecisionQ\u003cbr\u003e\n357.\tdeCode Genetics\u003cbr\u003e\n358.\tDeep Bio\u003cbr\u003e\n359.\tDeep Genomics\u003cbr\u003e\n360.\tDeep Longevity\u003cbr\u003e\n361.\tDeep Smart Light\u003cbr\u003e\n362.\tDeepCare\u003cbr\u003e\n363.\tDeepIntent\u003cbr\u003e\n364.\tDeepLife\u003cbr\u003e\n365.\tDeepNoid\u003cbr\u003e\n366.\tDeepWise\u003cbr\u003e\n367.\tDefiniens\u003cbr\u003e\n368.\tDefiniens\u003cbr\u003e\n369.\tDelphinus Medical Technologies\u003cbr\u003e\n370.\tDemala\u003cbr\u003e\n371.\tDenka\u003cbr\u003e\n372.\tDePuySynthes\u003cbr\u003e\n373.\tDexcom\u003cbr\u003e\n374.\tDiagnoplex\u003cbr\u003e\n375.\tDiagnoss\u003cbr\u003e\n376.\tDianon Systems\u003cbr\u003e\n377.\tDIG Labs\u003cbr\u003e\n378.\tDigiM Solution\u003cbr\u003e\n379.\tDigital Infuzion\u003cbr\u003e\n380.\tDigital Medical Experts\u003cbr\u003e\n381.\tDignity Health\u003cbr\u003e\n382.\tDirect Supply\u003cbr\u003e\n383.\tDisney Enterprises\u003cbr\u003e\n384.\tDM Intelligence\u003cbr\u003e\n385.\tDoAI\u003cbr\u003e\n386.\tDoc.Ai\u003cbr\u003e\n387.\tDommar\u003cbr\u003e\n388.\tDr. Eyal Bressler\u003cbr\u003e\n389.\tDräger\u003cbr\u003e\n390.\tDraper\u003cbr\u003e\n391.\tDrFirst\u003cbr\u003e\n392.\tDrishti\u003cbr\u003e\n393.\tDTN\u003cbr\u003e\n394.\tDuke University\u003cbr\u003e\n395.\tDyax\u003cbr\u003e\n396.\tDynamic Imaging\u003cbr\u003e\n397.\tDYSIS Medical \u003cbr\u003e\n398.\tDZee Solutions\u003cbr\u003e\n399.\tEBM Technologies\u003cbr\u003e\n400.\tEbonz \u003cbr\u003e\n401.\teCare21\u003cbr\u003e\n402.\tEchelonDx\u003cbr\u003e\n403.\tEcosense\u003cbr\u003e\n404.\tEDP Biotech\u003cbr\u003e\n405.\tEight Sleep\u003cbr\u003e\n406.\tEIO Diagnostics\u003cbr\u003e\n407.\tELC Management\u003cbr\u003e\n408.\tElectronics and Telecommunications Research Institute\u003cbr\u003e\n409.\tElekta\u003cbr\u003e\n410.\tElements of Genius\u003cbr\u003e\n411.\tEllipsis Health\u003cbr\u003e\n412.\tElucid\u003cbr\u003e\n413.\tElwha\u003cbr\u003e\n414.\tElwha\u003cbr\u003e\n415.\tEmbraer\u003cbr\u003e\n416.\tEMC Holdings\u003cbr\u003e\n417.\tEMED Technologies\u003cbr\u003e\n418.\tEmfit\u003cbr\u003e\n419.\tEmory University\u003cbr\u003e\n420.\tEmpire IP\u003cbr\u003e\n421.\teNano Health\u003cbr\u003e\n422.\tEndpoint Health\u003cbr\u003e\n423.\tEngauge\u003cbr\u003e\n424.\tEntelos\u003cbr\u003e\n425.\tEntelos Holding Corporation\u003cbr\u003e\n426.\tEntelos Holding Corporation\u003cbr\u003e\n427.\tEnvironmental Technologies Group\u003cbr\u003e\n428.\tEnvisagenics\u003cbr\u003e\n429.\tEPFL\u003cbr\u003e\n430.\tEQ Holdings\u003cbr\u003e\n431.\tEquity\u003cbr\u003e\n432.\teSentire\u003cbr\u003e\n433.\teSight Eyeware\u003cbr\u003e\n434.\tEssen BioScience\u003cbr\u003e\n435.\tEssenlix Corporation\u003cbr\u003e\n436.\tEstimo Healthcare\u003cbr\u003e\n437.\tETH Zurich\u003cbr\u003e\n438.\tEthicon \u003cbr\u003e\n439.\tEuclidSR Partners\u003cbr\u003e\n440.\tEuroproteome AG\u003cbr\u003e\n441.\tEvalytica\u003cbr\u003e\n442.\tEvidera\u003cbr\u003e\n443.\tEvogen \u003cbr\u003e\n444.\tExact Imaging\u003cbr\u003e\n445.\tExini\u003cbr\u003e\n446.\tEXINI Diagnostics\u003cbr\u003e\n447.\tExosome Diagnostics\u003cbr\u003e\n448.\tExperian Health\u003cbr\u003e\n449.\tExperTune \u003cbr\u003e\n450.\tExpress Scripts\u003cbr\u003e\n451.\tEyes, Japan\u003cbr\u003e\n452.\tFacebook Technology\u003cbr\u003e\n453.\tFacet\u003cbr\u003e\n454.\tFamily Inada\u003cbr\u003e\n455.\tFasotec\u003cbr\u003e\n456.\tFederral State Autonomous Educational Institution of Higher Education\u003cbr\u003e\n457.\tFEI Company\u003cbr\u003e\n458.\tFICO\u003cbr\u003e\n459.\tFirst Opinion\u003cbr\u003e\n460.\tFlatiron Health\u003cbr\u003e\n461.\tFujitsu\u003cbr\u003e\n462.\tGeisinger\u003cbr\u003e\n463.\tGenePlus\u003cbr\u003e\n464.\tGeneral Electric\u003cbr\u003e\n465.\tGeneType\u003cbr\u003e\n466.\tGeorgia Tech Research Institute\u003cbr\u003e\n467.\tGerman Cancer Research Center\u003cbr\u003e\n468.\tGerman Cancer Research Center\u003cbr\u003e\n469.\tGlobal Foundries\u003cbr\u003e\n470.\tGlobal Life Sciences Solutions USA\u003cbr\u003e\n471.\tGrail\u003cbr\u003e\n472.\tGrail\u003cbr\u003e\n473.\tGX Life Technology \u003cbr\u003e\n474.\tHarbin Institute of Technology\u003cbr\u003e\n475.\tHarvard\u003cbr\u003e\n476.\tHealth Diagnostic Laboratory\u003cbr\u003e\n477.\tHealth Dialog \u003cbr\u003e\n478.\tHealthTrio\u003cbr\u003e\n479.\tHealthways\u003cbr\u003e\n480.\tHeartFlow\u003cbr\u003e\n481.\tHighland Innovations\u003cbr\u003e\n482.\tHitachi\u003cbr\u003e\n483.\tHologic\u003cbr\u003e\n484.\tHuman Longevity\u003cbr\u003e\n485.\tHumana\u003cbr\u003e\n486.\tIBM\u003cbr\u003e\n487.\tIBM\u003cbr\u003e\n488.\tIcahn School of Medicine, Mt. Sinai\u003cbr\u003e\n489.\tImsight Technology\u003cbr\u003e\n490.\tIncluded Health\u003cbr\u003e\n491.\tInspirata\u003cbr\u003e\n492.\tInterleukin Genetics\u003cbr\u003e\n493.\tIntuit\u003cbr\u003e\n494.\tInvention Science Fund Incubator\u003cbr\u003e\n495.\tInvention Science Fund Incubator\u003cbr\u003e\n496.\tIQVIA\u003cbr\u003e\n497.\tJ. Morita USA\u003cbr\u003e\n498.\tJuno Therapeutics\u003cbr\u003e\n499.\tJurosense\u003cbr\u003e\n500.\tKnowledge Vision (Chengdu)\u003cbr\u003e\n501.\tKorea Advanced Institute of Science and Technology\u003cbr\u003e\n502.\tKPN Ventures\u003cbr\u003e\n503.\tLifeline Biotechnologies\u003cbr\u003e\n504.\tLifeQ\u003cbr\u003e\n505.\tLive Networks\u003cbr\u003e\n506.\tMayo Clinic\u003cbr\u003e\n507.\tMckesson\u003cbr\u003e\n508.\tMedis Medical Imaging\u003cbr\u003e\n509.\tMedtronic\u003cbr\u003e\n510.\tMemorial Sloan Kettering Cancer Center\u003cbr\u003e\n511.\tMentis Cura\u003cbr\u003e\n512.\tMerge\u003cbr\u003e\n513.\tMerit CRO\u003cbr\u003e\n514.\tMicroMass\u003cbr\u003e\n515.\tMicrosoft\u003cbr\u003e\n516.\tMoffitt Cancer Center\u003cbr\u003e\n517.\tNanjing Shihe Gene Biotechnology\u003cbr\u003e\n518.\tNantOmics\u003cbr\u003e\n519.\tNantWorks\u003cbr\u003e\n520.\tNational Center for Scientific Research, France\u003cbr\u003e\n521.\tNatural Institute for Health and Medical Research\u003cbr\u003e\n522.\tNavican\u003cbr\u003e\n523.\tNEC\u003cbr\u003e\n524.\tNew York Genome Center\u003cbr\u003e\n525.\tNorthrop Grumman\u003cbr\u003e\n526.\tOpko Diagnostics\u003cbr\u003e\n527.\tOptimata\u003cbr\u003e\n528.\tParadromics\u003cbr\u003e\n529.\tPatientsLikeMe\u003cbr\u003e\n530.\tPeraton\u003cbr\u003e\n531.\tPhilip Morris International\u003cbr\u003e\n532.\tPhilips\u003cbr\u003e\n533.\tPhilips\u003cbr\u003e\n534.\tProgenics Pharmaceuticals\u003cbr\u003e\n535.\tPsomagen\u003cbr\u003e\n536.\tPublic Health Research Center\u003cbr\u003e\n537.\tPulse Biosciences\u003cbr\u003e\n538.\tQuantum Leap Healthcare Collaborative\u003cbr\u003e\n539.\tReliance\u003cbr\u003e\n540.\tRicoh\u003cbr\u003e\n541.\tRoche\u003cbr\u003e\n542.\tRoche\u003cbr\u003e\n543.\tRoche\u003cbr\u003e\n544.\tSamsung Electronics\u003cbr\u003e\n545.\tSamsung Life Public Welfare Foundation\u003cbr\u003e\n546.\tSelvas AI\u003cbr\u003e\n547.\tSeoul National University\u003cbr\u003e\n548.\tShanghai Center for Bioinformation Technology\u003cbr\u003e\n549.\tShanghai Internationa Trading\u003cbr\u003e\n550.\tShimadzu Corporation\u003cbr\u003e\n551.\tSiemens\u003cbr\u003e\n552.\tSiemens Healthineers \u003cbr\u003e\n553.\tSmartMirror\u003cbr\u003e\n554.\tSmith+Nephew\u003cbr\u003e\n555.\tSmiths Detection\u003cbr\u003e\n556.\tSomaLogic\u003cbr\u003e\n557.\tSony\u003cbr\u003e\n558.\tSun Yat-Sen University Cancer Center\u003cbr\u003e\n559.\tSunnybrook Research Institute\u003cbr\u003e\n560.\tSurgical Theater\u003cbr\u003e\n561.\tSysmex\u003cbr\u003e\n562.\tTempus\u003cbr\u003e\n563.\tTerumo\u003cbr\u003e\n564.\tTethys Bioscience\u003cbr\u003e\n565.\tThe Hartford\u003cbr\u003e\n566.\tThe National Center for Scientific Research (CNRS)\u003cbr\u003e\n567.\tUniServices\u003cbr\u003e\n568.\tUniversity of Connecticut\u003cbr\u003e\n569.\tUniversity of Freiburg\u003cbr\u003e\n570.\tUniversity of Nebraska\u003cbr\u003e\n571.\tUniversity of New Mexico, Science \u0026amp; Technology Corporation\u003cbr\u003e\n572.\tUniversity of Texas\u003cbr\u003e\n573.\tWellvii\u003cbr\u003e\n574.\tWision AI\u003cbr\u003e\n575.\tZalicus\u003cbr\u003e\n576.\tZeiss\u003c\/p\u003e\n\n\u003cp\u003ePlease note that the publisher limits purchases by consulting clients to either Consulting Company Team License or Global Site License for Entire Company. Any other selections will not be fulfilled by this publisher.\u003c\/p\u003e","brand":"Service Industrries","offers":[{"title":"January, 2022 \/ 93 Pages \/ MCW16270248","offer_id":47707074298162,"sku":null,"price":1559.0,"currency_code":"USD","in_stock":true}],"url":"https:\/\/www.hardmanwell.com\/products\/artificial-intelligence-in-healthcare-intellectual-property-landscape","provider":"HARDMAN AND WELL MANAGEMENT CONSULTANCIES L.L.C","version":"1.0","type":"link"}